There does not currently exist a technology that predicts the course of aberrant fracture during the critically-important early healing phase (<4 weeks post-operative). This represents a significant clinical detriment and impedes decision-making with regard to whether the administration of additional therapies (such as biologics) should be implemented. Accordingly, we have previously developed a biocompatible, microelectromechanical rigid substrate sensor (bioMEMS) that telemetrically reports fracture fixation plate implant strain data. The overarching goal of this research endeavor is to evolve our innovative bioMEMS sensing technique into flexible multi-sensor configuration embodiments (fs-bioMEMS) in order to affect a significant improvement in post-surgical orthopaedic diagnostics. In this proposal, we seek to apply our bioMEMS technology to facilitate post-surgical diagnostics for two of the most prevalent orthopaedic fracture conditions in contemporary medicine (namely, difficult diaphyseal and metaphyseal fractures). There is a very high clinical demand for diagnosing early and aberrant fracture healing. The inability to detect these events is a major limiting step for implementing new and relatively non-invasive revision strategies. We have developed an innovative technology that seeks to overcome this challenge by reporting the transient load transfer profile between bone and implanted hardware. A unique embodiment of this technology includes using a flexible substrate that allows for implementation of the sensor architecture on implants with curved surfaces, providing implementation on a much broader range of implants including IM rods and curved fixation plates. Therefore, more challenging fracture patterns can be monitored during the early healing phase, including diaphyseal and supracondylar fractures. In addition, in order to overcome the considerable inherent variability associated with different loading conditions, our group has redesigned the sensor's circuit architecture to be responsive to principal strains. The proposed research seeks to further develop the fs-bioMEMS sensor architecture in order to optimize multi-sensing methods (Specific Aim 1) and use an in vivo platforms to evaluate the sensor's ability to monitor and predict fracture healing (Specific Aims 2 and 3). In addition to monitoring the healing cascade, we also propose to examine the intra- implant strain profiles and resultant healing effects associated with plates having different rigidities (Specific Aim 3) in order to address how different fractures could be more optimally treated